metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: balanced-augmented-roberta-gest-pred-seqeval-partialmatch-2
    results: []

balanced-augmented-roberta-gest-pred-seqeval-partialmatch-2

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5211
Precision: 0.9245
Recall: 0.9214
F1: 0.9159
Accuracy: 0.9027

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
3.0873	1.0	52	2.5606	0.1508	0.1205	0.1095	0.3096
2.2599	2.0	104	1.8545	0.3409	0.3827	0.3343	0.5265
1.7149	3.0	156	1.4711	0.5470	0.5222	0.4715	0.6087
1.3056	4.0	208	1.0879	0.6500	0.6103	0.5886	0.6919
0.9978	5.0	260	1.0036	0.7039	0.6766	0.6497	0.7221
0.7532	6.0	312	0.7722	0.7356	0.7552	0.7286	0.7842
0.5945	7.0	364	0.6766	0.8316	0.7902	0.7790	0.8053
0.473	8.0	416	0.5994	0.8602	0.8248	0.8224	0.8406
0.3762	9.0	468	0.5572	0.8725	0.8743	0.8600	0.8593
0.2943	10.0	520	0.5767	0.8893	0.8714	0.8659	0.8593
0.251	11.0	572	0.5480	0.8892	0.8765	0.8667	0.8633
0.2074	12.0	624	0.5652	0.8960	0.8866	0.8757	0.8714
0.1714	13.0	676	0.5254	0.9172	0.9087	0.9019	0.8875
0.1523	14.0	728	0.5788	0.9217	0.8900	0.8918	0.8790
0.1309	15.0	780	0.5209	0.9205	0.9141	0.9080	0.8961
0.1187	16.0	832	0.5030	0.9163	0.9138	0.9073	0.8961
0.1065	17.0	884	0.5449	0.9278	0.9212	0.9153	0.8986
0.0923	18.0	936	0.4965	0.9214	0.9180	0.9135	0.9012
0.0894	19.0	988	0.5171	0.9236	0.9189	0.9148	0.9007
0.0869	20.0	1040	0.5211	0.9245	0.9214	0.9159	0.9027

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2